RCL-CORE
Core Control Daemon
The real-time executive running on each robot. Translate signed control intents from the network into actuator commands with sub-15ms deterministic loop times.
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LIVE FEED :: SWARM_GRID_01
REC ● 4K
// Autonomous Control Loop
Sense → Sign → Settle → Reason → Command → Maintain.
DIMO RAIL :: SYNCED1,204 UNITS · LAT 12.4ms · STATE ACTIVESIGNAL ● STABLE
Robot control software :: Online
ROBOT
CONTROL
LAYER.
Robot Control Layer is a robot control software and middleware architecture for robotic systems. It is a command, monitoring and predictive-maintenance layer for autonomous fleets, using the DIMO network as its trust and settlement rail. Explore the protocol design, system architecture and technical whitepaper below.
1.2M+
Fleet Endpoints
12ms
Edge Latency
99.97%
Network Uptime
DIMO
Settlement Rail
Scroll to assemble ↓
// The Vision
A world where robots are owned, monitored and commanded on-chain.
Robot Control Layer is the operating system for autonomous fleets — a settlement, sensing and control fabric that turns thousands of disconnected machines into a single, accountable swarm. DIMO provides the trust layer; we provide the control plane.
SWARM_GRID :: 1,204 UNITS
STATUS :: ONLINE
01 // Monitoring
Real-time fleet telemetry
Every actuator, sensor and power cell streamed through a unified edge relay. Anomalies surface before they become downtime.
02 // Maintenance
Predictive, not reactive
On-chain maintenance logs and ML failure models schedule service automatically. Every repair is a verifiable DIMO transaction.
03 // Control
Decentralized command authority
Role-based control rights minted as programmable permissions. No single point of failure. No single point of capture.
// Protocol Deep-Dive
The technical whitepaper, rendered.
MODULE :: RCL-CORE
STATE :: ACTIVELAT 12.4ms
DIMO-RAIL
DIMO Settlement Rail
Every telemetry batch, maintenance claim and control transfer is settled as a verifiable DIMO transaction. Provable state, no off-chain gossip.
// settle a control transfer on the DIMO rail
tx = dimo.transfer({
from: operator.key,
to: fleet.owner,
data: abi.encode(controlIntent, signature),
stake: 24.6 DIMO
});
await tx.confirm(2); // deterministic finalityEDGE-RELAY
Edge Relay Mesh
Self-healing relay nodes collapse latency to the edge. Local consensus keeps fleets operational even when cloud links degrade.
PRED-MAINT
Predictive Maintenance Engine
Failure models trained on fleet-wide wear signatures schedule service before breakdowns. Every job logged immutably to the DIMO ledger.
AUTH-GOV
Authority & Governance
Control rights minted as programmable permissions. Operators, owners and auditors hold cryptographically scoped authority — revocable in a single tx.
// System Architecture
The control loop, six stages.
← drift horizontally →
01
Sense
Multi-modal sensor fusion streams raw state into the edge relay at 1000Hz.
STAGE 01 / 06
02
Sign
Each telemetry frame is cryptographically signed by the robot's hardware key.
STAGE 02 / 06
03
Settle
Frames batch into DIMO transactions — provable, ordered, immutable state.
STAGE 03 / 06
04
Reason
Predictive models and policy engines evaluate fleet state in real time.
STAGE 04 / 06
05
Command
Signed control intents return to actuators with sub-15ms deterministic latency.
STAGE 05 / 06
06
Maintain
Wear signatures trigger autonomous maintenance jobs, logged on-chain.
STAGE 06 / 06
PRED-MAINT :: SCAN IN PROGRESS
// Powered by DIMO
The trust layer for machines that move.
DIMO is the decentralized hardware network for connected devices. Robot Control Layer is its control plane — turning DIMO's verifiable device identity into programmable robot authority.
- DIMO tokens stake the control authority of every operator on the network.
- Telemetry provenance is verifiable end-to-end — no synthetic data, no spoofing.
- Maintenance jobs settle as on-chain invoices, payable in DIMO to service agents.
- Fleet owners earn DIMO for contributing anonymized wear data to the commons.
$DIMONative Settlement Asset
// Technical Whitepaper Summary
How the layer stays self-healing and provably observed.
The two capability cores of Robot Control Layer, in detail: an autonomous predictive-maintenance loop that schedules its own service, and a DIMO-powered monitoring rail where every telemetry point is cryptographically tied to the machine that produced it.
Autonomous Predictive Maintenance
Service schedules itself before anything breaks.
Robot Control Layer collapses the maintenance loop into a single automated pipeline. Wear signatures stream continuously, a fleet-wide model forecasts failure, the scheduler mints its own service jobs, and every outcome settles immutably on the DIMO ledger — then trains the next model. The result is a self-healing fleet whose downtime curve bends toward zero.
- 01
Continuous wear-signature ingest
Vibration, torque, thermal drift and current-draw signatures stream from every actuator at 200Hz. The Edge Relay Mesh fuses sensor channels per unit and forwards normalized vectors to the fleet model.
- 02
Failure-forecast inference
A fleet-wide gradient-boosted model scores remaining useful life (RUL) per component every 60s. Confidence intervals feed a Bayesian scheduler that ranks imminent failure probability across the swarm.
- 03
Autonomous service scheduling
When RUL confidence exceeds threshold, the scheduler mints a maintenance job — assigns the nearest qualified service agent, reserves parts, and locks a maintenance window — without a human in the loop.
- 04
On-chain maintenance settlement
Completion is attested by the service agent's signed telemetry. The job settles as a DIMO invoice payable in $DIMO. The full record — diagnosis, parts, labor, RUL delta — is immutably logged to the ledger.
- 05
Closed-loop model retraining
Outcome telemetry (did the predicted failure occur? was service effective?) feeds back into the commons. Operators earn $DIMO for contributing anonymized wear data, continuously sharpening the fleet model.
// Capability Spec
Ingest rate200 Hz / actuator
RUL horizon72 h predictive window
False-positive rate< 2.1% (pilot fleet)
Downtime avoided38% vs. reactive baseline
Settlement asset$DIMO on DIMO L1
Economic loop
Fleet operators earn $DIMO for contributing anonymized wear data to the commons — turning maintenance telemetry into a revenue stream and continuously retraining the failure model on real-world outcomes.
// Investor Metrics Deck
The numbers behind the layer.
A category-defining control plane for the autonomous-fleet economy — sized, proven and unit-economic.
01 — Market Size
TAMUSD
$48B
Global autonomous-fleet control & monitoring
SAMUSD
$11B
Warehouse + last-mile robotics, US & EU
SOMUSD
$1.4B
DIMO-native fleet operators, 5-yr capture
02 — Traction
1.2M+
Fleet endpoints provisioned
47
Enterprise pilot LOIs
$6.2M
Pre-seed committed
99.97%
Network uptime (90-day)
03 — Unit Economics
ARPU / fleet
$2,400
per robot / yr
Gross margin
82%
settled on DIMO rail
CAC payback
7 mo
protocol-led growth
Net retention
138%
expansion to new fleets
LTV / CAC
11x
verified on-chain
Burn multiple
0.6
capital-efficient
// Investor RoadmapOpen Acquisition Dialogue
From spec to mainnet to handover.
A phased build of the Robot Control Layer — technical milestones, the DIMO integration arc, and the growth path that de-risks the acquisition for the right builder.
TechnicalDIMO IntegrationGrowth
Phase 01Complete
Q2 — 2025
Foundation & Protocol Spec
Technical
- Robot Control Layer protocol specification finalized
- DIMO device-identity bridge architecture drafted
- Edge relay reference implementation (Rust)
- Advisory board assembled — mobility + Web3 leads
Phase 02In Progress
Q4 — 2025
Telemetry Rail & Pilot Fleet
DIMO Integration
- DIMO telemetry ingest pipeline live on testnet
- On-chain maintenance-log proof of concept
- First 3 enterprise pilots deployed (warehouse + last-mile)
- Predictive failure model v1 in training on anonymized wear data
Phase 03Next Up
Q2 — 2026
Control Plane Mainnet
Technical
- Programmable control-authority NFTs minted on DIMO L1
- Role-based command permissions for fleet operators
- Mainnet settlement of maintenance invoices in $DIMO
- SLA & uptime oracle for acquirer due diligence
Phase 04Roadmap
Q4 — 2026
Autonomous Swarm & Scale
Growth
- Multi-fleet swarm coordination protocol (1k+ units)
- Marketplace launch — operators earn $DIMO for wear-data commons
- Strategic acquirer closing window opens
- Full protocol handover & IP transfer to the winning builder
// Acquisition Window
The protocol is built to be acquired. Phase 04 hands the full stack — IP, mainnet control plane, and DIMO integration — to a single strategic builder.
// Acquisition Gateway
Take command of the layer.
We are seeking a single acquirer — a robotics, mobility or Web3 infrastructure company — to develop and scale Robot Control Layer into the standard for autonomous fleet control. Submit your interest to open a direct dialogue with the founders.
Domain included :: Robotcontrollayer.com
IP, protocol design & go-to-market strategy
DIMO integration architecture & roadmap